ymanatos1 / practicalml

Assignment: Practical Machine Learning Course Project

for the course "Practical Machine Learning"

of "Data Science Specialization" specialization.

By Yiannis Manatos, December 10, 2016

Abstract

This is my Project submission, containing the following files and folders:

A) Project data files:

1. pml-training.csv

2. pml-testing.csv

B) Project report files:

1. PracticalML-Project.html : The project report (HTML format).

2. PracticalML-Project.pdf : The project report (pdf format).

3. PracticalML-Project.Rmd : The project R-markdown file (needs about 10 minutes or more to run).

4. README.md : This readme file.

Synopsis

This report analyzes data collected from belt, forearm, arm, and dumbbell accelerometers of 6 participants, in order to predict the manner in which they did their exercise. Participants were asked to perform one set of 10 repetitions of the Unilateral Dumbbell Biceps Curl in five different fashions: exactly according to the specification (Class A), throwing the elbows to the front (Class B), lifting the dumbbell only halfway (Class C), lowering the dumbbell only halfway (Class D) and throwing the hips to the front (Class E). Class A corresponds to the specified execution of the exercise, while the other 4 classes correspond to common mistakes.

Using devices such as Jawbone Up, Nike FuelBand, and Fitbit it is now possible to collect a large amount of data about personal activity relatively inexpensively. These type of devices are part of the quantified self movement – a group of enthusiasts who take measurements about themselves regularly to improve their health, to find patterns in their behavior, or just because they are tech geeks. One thing that people regularly do is quantify how much of a particular activity they do, but they rarely quantify how well they do it. In this project, your goal will be to use data from accelerometers on the belt, forearm, arm, and dumbell of 6 participants, and predict the manner in which participants did the exercise. The classe variable in the training set takes on 1 of the 5 Classes (i.e. A, B, C, D, E).

More information is available from the website here: http://groupware.les.inf.puc-rio.br/har (see the section on the Weight Lifting Exercise Dataset).

Data

The training data for this project are available here: https://d396qusza40orc.cloudfront.net/predmachlearn/pml-training.csv.

The test data are available here: https://d396qusza40orc.cloudfront.net/predmachlearn/pml-testing.csv

The data for this project come from this source: http://groupware.les.inf.puc-rio.br/har. If you use the document you create for this class for any purpose please cite them as they have been very generous in allowing their data to be used for this kind of assignment.

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